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Titlebook: Religion, Kultur und Politik im Vorderen Orient; Die Islamische Welt Peter Pawelka,Lutz Richter-Bernburg Book 2004 VS Verlag für Sozialwis

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Islamismus im Kontext der Globalisierung, keinen konkreten Akteur (ein Regime, staatliche Institutionen oder das Militär) im Visier, sondern konstruiert vor allem kulturelle Institutionen als symbolisches Operationsziel ohne einen spezifischen Ortsbezug. Islamistische Deutungen solcher Netzwerke wie die von al-Qaida beruhen auf einer für d
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Udo Steinbachc about 0 and for detecting location change or scale change in an arbitrary unknown distribution. These stopping rules are defined on doubly-indexed stochastic processes whose weak limits are derived when there is no change and when there is a contiguous change. New fluctuation inequalities for rank
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Eberhard Kienlen distribution function. As shown by Qin and Lawless in (Ann Statist 22:300–325, .), in the presence of some nonparametric auxiliary information about the underlying distribution function the nonparametric maximum likelihood estimator is a modified empirical distribution function. It puts random mas
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Helga Baumgartenc about 0 and for detecting location change or scale change in an arbitrary unknown distribution. These stopping rules are defined on doubly-indexed stochastic processes whose weak limits are derived when there is no change and when there is a contiguous change. New fluctuation inequalities for rank
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Martin Beckc about 0 and for detecting location change or scale change in an arbitrary unknown distribution. These stopping rules are defined on doubly-indexed stochastic processes whose weak limits are derived when there is no change and when there is a contiguous change. New fluctuation inequalities for rank
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Lutz Richter-Bernburgdimensional) function as a decomposition/superposition of simpler (low-dimensional) basis functions. Such methods naturally follow the supervised learning paradigm. In this paper we discuss a different approach to nonparametric regression that is based on unsupervised learning. Unsupervised learning
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